




"""simple docstring"""





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
					from PIL import Image

					from transformers import OwlViTImageProcessor, OwlViTProcessor



@require_vision
class   a__					(						unittest.TestCase ):


			def    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase						:			str												=       tempfile.mkdtemp()

						# fmt: off
						__UpperCAmelCase						:			List[Any]												=       ["", "l", "o", "w", "e", "r", "s", "t", "i", "d", "n", "lo", "l</w>", "w</w>", "r</w>", "t</w>", "low</w>", "er</w>", "lowest</w>", "newer</w>", "wider", "<unk>", "<|startoftext|>", "<|endoftext|>"]
						# fmt: on
						__UpperCAmelCase						:			Union[str, Any]												=       dict(zip(UpperCamelCase_   ,	range(len(UpperCamelCase_))))
						__UpperCAmelCase						:			Dict												=       ["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
						__UpperCAmelCase						:			str												=       {"unk_token": "<unk>"}

						__UpperCAmelCase						:			str												=       os.path.join(self.tmpdirname   ,	VOCAB_FILES_NAMES["vocab_file"])
						__UpperCAmelCase						:			List[str]												=       os.path.join(self.tmpdirname   ,	VOCAB_FILES_NAMES["merges_file"])
						with open(self.vocab_file   ,	"w"   ,	encoding="utf-8") as fp:
									fp.write(json.dumps(UpperCamelCase_) + "\n")
						with open(self.merges_file   ,	"w"   ,	encoding="utf-8") as fp:
									fp.write("\n".join(UpperCamelCase_))

						__UpperCAmelCase						:			str												=       {
						    "do_resize": True,
						    "size": 20,
						    "do_center_crop": True,
						    "crop_size": 18,
						    "do_normalize": True,
						    "image_mean": [0.48145466, 0.4578275, 0.40821073],
						    "image_std": [0.26862954, 0.26130258, 0.27577711],
						}
						__UpperCAmelCase						:			List[Any]												=       os.path.join(self.tmpdirname   ,	UpperCamelCase_)
						with open(self.image_processor_file   ,	"w"   ,	encoding="utf-8") as fp:
									json.dump(UpperCamelCase_   ,	UpperCamelCase_)


			def    a_  (   self   :     Any   ,	**UpperCamelCase_   :     Dict):


						"""simple docstring"""




						return CLIPTokenizer.from_pretrained(self.tmpdirname   ,	pad_token="!"   ,	**UpperCamelCase_)


			def    a_  (   self   :     Union[str, Any]   ,	**UpperCamelCase_   :     List[Any]):


						"""simple docstring"""




						return CLIPTokenizerFast.from_pretrained(self.tmpdirname   ,	pad_token="!"   ,	**UpperCamelCase_)


			def    a_  (   self   :     Tuple   ,	**UpperCamelCase_   :     Union[str, Any]):


						"""simple docstring"""




						return OwlViTImageProcessor.from_pretrained(self.tmpdirname   ,	**UpperCamelCase_)


			def    a_  (   self   :     Union[str, Any]):


						"""simple docstring"""




						shutil.rmtree(self.tmpdirname)


			def    a_  (   self   :     str):


						"""simple docstring"""




						__UpperCAmelCase						:			Dict												=       [np.random.randint(255   ,	size=(3, 30, 400)   ,	dtype=np.uinta)]

						__UpperCAmelCase						:			List[str]												=       [Image.fromarray(np.moveaxis(UpperCamelCase_   ,	0   ,	-1)) for x in image_inputs]

						return image_inputs


			def    a_  (   self   :     Union[str, Any]):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       self.get_tokenizer()
						__UpperCAmelCase						:			int												=       self.get_rust_tokenizer()
						__UpperCAmelCase						:			int												=       self.get_image_processor()

						__UpperCAmelCase						:			Tuple												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)
						processor_slow.save_pretrained(self.tmpdirname)
						__UpperCAmelCase						:			Union[str, Any]												=       OwlViTProcessor.from_pretrained(self.tmpdirname   ,	use_fast=UpperCamelCase_)

						__UpperCAmelCase						:			List[Any]												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)
						processor_fast.save_pretrained(self.tmpdirname)
						__UpperCAmelCase						:			Optional[Any]												=       OwlViTProcessor.from_pretrained(self.tmpdirname)

						self.assertEqual(processor_slow.tokenizer.get_vocab()   ,	tokenizer_slow.get_vocab())
						self.assertEqual(processor_fast.tokenizer.get_vocab()   ,	tokenizer_fast.get_vocab())
						self.assertEqual(tokenizer_slow.get_vocab()   ,	tokenizer_fast.get_vocab())
						self.assertIsInstance(processor_slow.tokenizer   ,	UpperCamelCase_)
						self.assertIsInstance(processor_fast.tokenizer   ,	UpperCamelCase_)

						self.assertEqual(processor_slow.image_processor.to_json_string()   ,	image_processor.to_json_string())
						self.assertEqual(processor_fast.image_processor.to_json_string()   ,	image_processor.to_json_string())
						self.assertIsInstance(processor_slow.image_processor   ,	UpperCamelCase_)
						self.assertIsInstance(processor_fast.image_processor   ,	UpperCamelCase_)


			def    a_  (   self   :     List[str]):


						"""simple docstring"""




						__UpperCAmelCase						:			List[Any]												=       OwlViTProcessor(tokenizer=self.get_tokenizer()   ,	image_processor=self.get_image_processor())
						processor.save_pretrained(self.tmpdirname)

						__UpperCAmelCase						:			Dict												=       self.get_tokenizer(bos_token="(BOS)"   ,	eos_token="(EOS)")
						__UpperCAmelCase						:			str												=       self.get_image_processor(do_normalize=UpperCamelCase_)

						__UpperCAmelCase						:			Any												=       OwlViTProcessor.from_pretrained(
						    self.tmpdirname   ,	bos_token="(BOS)"   ,	eos_token="(EOS)"   ,	do_normalize=UpperCamelCase_)

						self.assertEqual(processor.tokenizer.get_vocab()   ,	tokenizer_add_kwargs.get_vocab())
						self.assertIsInstance(processor.tokenizer   ,	UpperCamelCase_)

						self.assertEqual(processor.image_processor.to_json_string()   ,	image_processor_add_kwargs.to_json_string())
						self.assertIsInstance(processor.image_processor   ,	UpperCamelCase_)


			def    a_  (   self   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			int												=       self.get_image_processor()
						__UpperCAmelCase						:			List[str]												=       self.get_tokenizer()

						__UpperCAmelCase						:			Optional[int]												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)

						__UpperCAmelCase						:			str												=       self.prepare_image_inputs()

						__UpperCAmelCase						:			Union[str, Any]												=       image_processor(UpperCamelCase_   ,	return_tensors="np")
						__UpperCAmelCase						:			List[str]												=       processor(images=UpperCamelCase_   ,	return_tensors="np")

						for key in input_image_proc.keys():
									self.assertAlmostEqual(input_image_proc[key].sum()   ,	input_processor[key].sum()   ,	delta=1e-2)


			def    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase						:			Optional[int]												=       self.get_image_processor()
						__UpperCAmelCase						:			Union[str, Any]												=       self.get_tokenizer()

						__UpperCAmelCase						:			str												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)

						__UpperCAmelCase						:			Tuple												=       "lower newer"

						__UpperCAmelCase						:			List[Any]												=       processor(text=UpperCamelCase_   ,	return_tensors="np")

						__UpperCAmelCase						:			Any												=       tokenizer(UpperCamelCase_   ,	return_tensors="np")

						for key in encoded_tok.keys():
									self.assertListEqual(encoded_tok[key][0].tolist()   ,	encoded_processor[key][0].tolist())


			def    a_  (   self   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			List[Any]												=       self.get_image_processor()
						__UpperCAmelCase						:			int												=       self.get_tokenizer()

						__UpperCAmelCase						:			Tuple												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)

						__UpperCAmelCase						:			Union[str, Any]												=       "lower newer"
						__UpperCAmelCase						:			str												=       self.prepare_image_inputs()

						__UpperCAmelCase						:			Any												=       processor(text=UpperCamelCase_   ,	images=UpperCamelCase_)

						self.assertListEqual(list(inputs.keys())   ,	["input_ids", "attention_mask", "pixel_values"])

						# test if it raises when no input is passed
						with pytest.raises(UpperCamelCase_):
									processor()


			def    a_  (   self   :     str):


						"""simple docstring"""




						__UpperCAmelCase						:			Dict												=       "google/owlvit-base-patch32"
						__UpperCAmelCase						:			str												=       OwlViTProcessor.from_pretrained(UpperCamelCase_)

						__UpperCAmelCase						:			int												=       ["cat", "nasa badge"]
						__UpperCAmelCase						:			Dict												=       processor(text=UpperCamelCase_)

						__UpperCAmelCase						:			List[Any]												=       16
						self.assertListEqual(list(inputs.keys())   ,	["input_ids", "attention_mask"])
						self.assertEqual(inputs["input_ids"].shape   ,	(2, seq_length))

						# test if it raises when no input is passed
						with pytest.raises(UpperCamelCase_):
									processor()


			def    a_  (   self   :     Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase						:			List[Any]												=       "google/owlvit-base-patch32"
						__UpperCAmelCase						:			Tuple												=       OwlViTProcessor.from_pretrained(UpperCamelCase_)

						__UpperCAmelCase						:			Optional[int]												=       [["cat", "nasa badge"], ["person"]]
						__UpperCAmelCase						:			List[str]												=       processor(text=UpperCamelCase_)

						__UpperCAmelCase						:			List[str]												=       16
						__UpperCAmelCase						:			str												=       len(UpperCamelCase_)
						__UpperCAmelCase						:			List[str]												=       max([len(UpperCamelCase_) for texts in input_texts])

						self.assertListEqual(list(inputs.keys())   ,	["input_ids", "attention_mask"])
						self.assertEqual(inputs["input_ids"].shape   ,	(batch_size * num_max_text_queries, seq_length))

						# test if it raises when no input is passed
						with pytest.raises(UpperCamelCase_):
									processor()


			def    a_  (   self   :     List[str]):


						"""simple docstring"""




						__UpperCAmelCase						:			Tuple												=       "google/owlvit-base-patch32"
						__UpperCAmelCase						:			Dict												=       OwlViTProcessor.from_pretrained(UpperCamelCase_)

						__UpperCAmelCase						:			Any												=       ["cat", "nasa badge"]
						__UpperCAmelCase						:			Optional[int]												=       processor(text=UpperCamelCase_)

						__UpperCAmelCase						:			Optional[int]												=       16
						__UpperCAmelCase						:			Optional[Any]												=       inputs["input_ids"]
						__UpperCAmelCase						:			Any												=       [
						    [49406, 2368, 49407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
						    [49406, 6841, 11301, 49407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
						]

						self.assertListEqual(list(inputs.keys())   ,	["input_ids", "attention_mask"])
						self.assertEqual(inputs["input_ids"].shape   ,	(2, seq_length))
						self.assertListEqual(list(input_ids[0])   ,	predicted_ids[0])
						self.assertListEqual(list(input_ids[1])   ,	predicted_ids[1])


			def    a_  (   self   :     int):


						"""simple docstring"""




						__UpperCAmelCase						:			Any												=       self.get_image_processor()
						__UpperCAmelCase						:			Any												=       self.get_tokenizer()

						__UpperCAmelCase						:			Tuple												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)

						__UpperCAmelCase						:			Any												=       self.prepare_image_inputs()
						__UpperCAmelCase						:			List[Any]												=       self.prepare_image_inputs()

						__UpperCAmelCase						:			Optional[Any]												=       processor(images=UpperCamelCase_   ,	query_images=UpperCamelCase_)

						self.assertListEqual(list(inputs.keys())   ,	["query_pixel_values", "pixel_values"])

						# test if it raises when no input is passed
						with pytest.raises(UpperCamelCase_):
									processor()


			def    a_  (   self   :     Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase						:			Optional[Any]												=       self.get_image_processor()
						__UpperCAmelCase						:			str												=       self.get_tokenizer()

						__UpperCAmelCase						:			str												=       OwlViTProcessor(tokenizer=UpperCamelCase_   ,	image_processor=UpperCamelCase_)

						__UpperCAmelCase						:			Tuple												=       [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

						__UpperCAmelCase						:			List[str]												=       processor.batch_decode(UpperCamelCase_)
						__UpperCAmelCase						:			Optional[int]												=       tokenizer.batch_decode(UpperCamelCase_)

						self.assertListEqual(UpperCamelCase_   ,	UpperCamelCase_)



import functools
from typing import Any


def 	lowerCamelCase					(	UpperCamelCase     :				str			,       UpperCamelCase     :				list[str]							)   ->    bool:

		# Validation
		if not isinstance(UpperCamelCase			,       UpperCamelCase							) or len(UpperCamelCase							) == 0:
				raise ValueError('the string should be not empty string'							)

		if not isinstance(UpperCamelCase			,       UpperCamelCase							) or not all(
		    isinstance(UpperCamelCase			,       UpperCamelCase							) and len(UpperCamelCase							) > 0 for item in words							):
				raise ValueError('the words should be a list of non-empty strings'							)

		# Build trie
		_lowerCamelCase				   =  {}
		_lowerCamelCase				   =  'WORD_KEEPER'

		for word in words:
				_lowerCamelCase				   =  trie
				for c in word:
						if c not in trie_node:
								_lowerCamelCase				   =  {}

						_lowerCamelCase				   =  trie_node[c]

				_lowerCamelCase				   =  True

		_lowerCamelCase				   =  len(UpperCamelCase							)

		# Dynamic programming method
		@functools.cache
		def is_breakable(UpperCamelCase     :				int							) -> bool:
				if index == len_string:
						return True

				_lowerCamelCase				   =  trie
				for i in range(UpperCamelCase			,       UpperCamelCase							):
						_lowerCamelCase				   =  trie_node.get(string[i]			,       UpperCamelCase							)

						if trie_node is None:
								return False

						if trie_node.get(UpperCamelCase			,       UpperCamelCase							) and is_breakable(i + 1							):
								return True

				return False

		return is_breakable(0							)


if __name__ == "__main__":
				import doctest

				doctest.testmod()